Abstract:
In current engineering practice, the estimation of extreme events such as extreme rainfall is accomplished based on statistical frequency analysis of maximum rainfall records where available sample data could be used to calculate the parameters of a selected frequency distribution. The study of frequency analysis is important to find the most suitable model that could anticipate extreme events of certain natural phenomena such as rainfall and floods. The objective of this study is to determine the best fit probability distributions in the case of maximum monthly rainfall using 30 years of data for Ibadan, Nigeria. Five commonly used probability distributions were applied. The parameters of these distributions were estimated and three Goodness of Fit Tests were used. The analysis was done using R studio programming language and Easy-Fit statistical software. The best fit distribution of each test was taken as the distribution with the lowest sum of the rank scores from each of the three test statistics. For Kolmogorov-Smirnov and Chi-Square test, normal distribution emerged as the best fit probability distribution. The Anderson-Darling test showed that log-normal distribution was the best fit distribution. Hence, The overall ranking showed normal distribution to be the best fit probability distribution that best suit the characteristics of the historical data being considered. The fitted distribution which was later used to estimate the maximum monthly rainfall of specific return periods showed that maximum rainfall depth of 5, 10, 25, 50 and 100 years return period were estimated to be 319, 339, 359, 373, and 385 mm respectively. The results of this study can be used to develop more accurate models of flooding risk and damage and the predicted future years maximum rainfall events would be useful for engineering planning and design of water resources project such as Dam design and construction, Spillway design, design of culverts and so on by government and private agencies.
